1. Comparison of Recorded and Simulated Ground Motions Presented by: Emel Seyhan, PhD Student University of California, Los Angeles Collaborators: Lisa M. Star, PhD Candidate, University of California, Los Angeles Robert W. Graves, PhD, USGS Jonathan P. Stewart, PhD, PE, University of California, Los Angeles

2. Outline Motivation Hybrid Simulation Procedure Validation Analysis & Results Distance scaling Standard deviation Calibration of Hybrid Simulation Procedure Distance attenuation Standard deviation Conclusions

3. Motivation Broadband motions for response history analysis Some (M, R) ranges poorly sampled by recordings Motions needed with specific attributes, e.g. Basin effect Near fault effects

4. Motivation Broadband motions for response history analysis Some (M, R) ranges poorly sampled by recordings Motions needed with specific attributes, e.g. Basin effect Near fault effects Simulations hold potential to provide useful ground motions for engineering application in these situations

5. ShakeOut Scenario Description Moment magnitude 7.8 earthquake 150 yr return period (last events 1857 & 1680) Evaluated for three different possible hypocenters Hughes Lake San Gorgonio Pass Bombay Beach

6. Puente Hills Scenario Directly under down town Los Angeles 7.15 M w Earthquake Buried reverse fault

7. Simulation Procedure Hybrid procedure f<1 Hz: physics based Physics-based

8. Simulation Procedure Hybrid procedure f<1 Hz: physics based f>1 Hz: stochastic Stochastic Reference: Graves et al, 2004

9. Simulation Procedure Hybrid procedure f<1 Hz: physics based f>1 Hz: stochastic Reference: Graves et al, 2004

10. Simulation Procedure Hybrid procedure Source function Kinematically prescribed source model Slip distribution Rupture velocity ShakeOut, M w 7.8

11. Hybrid procedure Source function Semi-empirical site term (fn of V s30 ) Simulation Procedure

12. Distance Attenuation

13. Calibration Analysis Approach Calculate residuals 4 GMPEs: AS, BA, CB, CY Random effect analysis: Separate event term (  i ) from within-event residual (  i,j ) Distance-scaling evaluated from (  i,j )

14. Calibration Analysis General Model  i,j = R i,j -  i

15. Intra-event Residuals

16. Intra-event Standard Deviation  too low for T < 1.0 s Large transition at T=1.0 s  =stdev(  )

17. Calibration of Hybrid Simulation Procedure Focus on high frequency stochastic model Controlling parameters Source parameters: Stress drop, slip function, rise time, rupture velocity Path parameters: Distance, crustal velocity & damping (Q) Site parameters: Near surface crustal velocity, shallow site term (V s30 ) Parameter selected for remove distance attenuation bias Procedure to increase intra-event standard deviation

18. Scope Distance attenuation calibration Strike slip fault M5, 6.5, 7.25 and 8 Distributed arrays M5M6.5M7.25M8

19. Slip models For M5, 6.5, 7.25 and 8 Random slips M5 M6.5

20. M7.25 M8

21. Various levels of crustal damping, Q Low Q o (a=25) Mid Q o (a=41) High Q o (a=57) Q (f) = Q o *f n (n = 0.6) Q o = a + b*V s (b = 34) ShakeOut

22. Verification of Hybrid Trends Using Stochastic Part Only Using same level of Q (Low Q o ) Original ShakeOut This study (M8) similar trend with previous work esp. beyond about 10 km

23. Removing Distance Attenuation Bias Comparing different level of Q (M7.25) Using low Q o Using high Q o

24. Removing Distance Attenuation Bias Residuals for different level of Q (M7.25) Using low Q o Using high Q o

25. Removing Distance Attenuation Bias Fit semi-log line to residuals of average ground motions For different level of Q Using low Q o Using high Q o Repeat for all M, GMPEs, IMs Y = c*ln(X) + d

26. Removing Distance Attenuation Bias Slope of residuals of average ground motions Scatter based on all gmpes Using low Q o Using high Q o PGA

27. Removing Distance Attenuation Bias Slope of residuals of average responses Using low Q o Using high Q o

28. Intra-event scatter calibration Increasing intra-event standard deviation Randomized velocity Randomized Fourier Amplitude Randomized Q

29. Approach Modify parameters e.g. Velocity profile Intra-event scatter calibration Rand Case NonRand Case BA08

30. Approach Randomization of Fourier Amplitude Adding variation Intra-event scatter calibration

31. Approach Randomization of Fourier Amplitude Adding variation Intra-event scatter calibration Rand Case NonRand Case BA08

32. Concluding Remarks Calibrated simulation procedures needed for engineering practice Validation process reveals: Faster distance attenuation at shorter periods Low intra-event standard deviation T<1s

33. Cont’d Calibration process reveals: Possible to get slower distance attenuation by using higher Q Randomization of Fourier Spectrum gives better results than randomization of velocity

34. More? Implementation fully hybrid simulation with revised Q and Vs

35. Thank you